


 Integral operator quality from low order interpolation
or
Sometimes nearest neighbor beats linear interpolation  

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Integral operator quality from low order interpolation
or
Sometimes nearest neighbor beats linear interpolation
Stewart A. Levin
Abstract:
In most discussions of interpolation methods, it is the worstcase behavior
that dominates the analysis. From a systems point of view, one really
should analyze how that interpolation is used in producing an end product
in order to determine the interpolation's suitability. In this report I
look at the summation operators slant stack, NMO and Kirchhoff migration
as the ``systems'' and
determine that their output quality can be significantly better than
the traditional take on interpolation would suggest. In one scenario,
I even found nearest neighbor interpolation did the job even better than
linear interpolation.
20120510